The Influence of Organic Acid on Thermal Aging of Power Transformer Oil-paper Insulation

AbstractInsulating paper is a traditional insulation material used for transformer insulation. Transformer development is not only limited to small sizes and large capacities, but also limited to insulation life as insulating paper cannot withstand high temperatures. Therefore, recent studies have focused on improving the performance of insulation paper and discovering better insulation materials. In this study, two types of polymeric materials, polycarbonate (PC) and polyester film (PET), were chosen for comparative analysis. In order to test whether these two materials could be used in oil-immersed transformers, the PC and PET were placed in transformer oil for thermal aging at 110°C and 130°C, respectively. The thermal cracking processes and fragmentation mechanisms of the PC, PET, and insulation paper were analyzed using thermal gravimetric analysis (TGA), differential scanning calorimetry (DSC), and atomic force microscopy (AFM), as well as their degrees of polymerization and surface morphologies. According to the test results, the initial thermal decomposition temperature of PC and PET are higher than insulation paper and exhibited a better thermal resistance. PC and PET have the potential to substitute insulation paper for large capacity power transformer.

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Terahertz Time Domain Spectroscopy of Transformer Insulation Paper after Thermal Aging Intervals

Materials ◽

10.3390/ma11112124 ◽

2018 ◽

Vol 11 (11) ◽

pp. 2124 ◽

Cited By ~ 9

Author(s):

Liang Wang ◽

Chao Tang ◽

Shiping Zhu ◽

Shengling Zhou

Keyword(s):

Time Domain ◽

Thermal Aging ◽

Density Functional ◽

Degree Of Polymerization ◽

Transformer Oil ◽

Optical Parameters ◽

Terahertz Time Domain Spectroscopy ◽

Time Domain Spectroscopy ◽

Paper Insulation ◽

Transformer Insulation

An accelerated thermal aging process was used to simulate the condition of paper insulation in transformer oil-paper systems. Optical parameters of the insulation paper after various aging intervals were analyzed with terahertz time-domain spectroscopy (THz-TDS) over the range 0.1~1.8 THz. The result shows that the paper had seven absorption peaks at 0.19, 0.49, 0.82, 1.19, 1.43, 1.53, and 1.74 THz, and density functional theory of B3LYP/6-311G+ (d, p) was used to simulate the molecular dynamics of the repeating component (cellobiose) of the cellulose paper. Theoretical spectra were consistent with experiment, which had absorption peaks at 0.18, 0.82, 1.47, and 1.53 THz in the same frequency range. At the same time, the paper samples after various aging intervals had different refractive indexes, and least squares fitting revealed a linear relationship between the degree of polymerization and the refractive index of the paper. Hence, this paper demonstrates that THz-TDS could be used to analyze the aging condition of transformer insulation paper and provides the theoretical and experimental basis for detection.

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Hot Spot Temperature and Grey Target Theory Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study

10.20944/preprints201801.0122.v1 ◽

2018 ◽

Author(s):

Lefeng Cheng ◽

Tao Yu ◽

Guoping Wang ◽

Bo Yang ◽

Lv Zhou

Keyword(s):

Life Expectancy ◽

Power Transformer ◽

Hot Spot ◽

Reliability Assessment ◽

Transformer Oil ◽

Practical Case ◽

Dynamic Correction ◽

Target Theory ◽

Paper Insulation

This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS) as the target of evaluation and the winding hot spot temperature (HST) as the core point, an HST-based static ageing failure model is built according to the Weibull distribution and Arrhenius reaction law, in order to describe the transformer ageing process and calculate the winding HST for obtaining the failure rate and life expectancy of TOPIS. A grey target theory based dynamic correction model is then developed, combined with the data of Dissolved Gas Analysis (DGA) in power transformer oil, in order to dynamically modify the life expectancy calculated by the built static model, such that the corresponding relationship between the state grade and life expectancy correction coefficient of TOPIS can be built. Furthermore, the life expectancy loss recovery factor is introduced to correct the life expectancy of TOPIS again. Lastly, a practical case study of an operating transformer has been undertaken, in which the failure rate curve after introducing dynamic corrections can be obtained for the reliability assessment of this transformer. The curve shows a better ability of tracking the actual reliability level of transformer, thus verifying the validity of the proposed method and providing a new way for transformer reliability assessment. This contribution presents a novel model for the reliability assessment of TOPIS, in which the DGA data, as a source of information for the dynamic correction, is processed based on the grey target theory, thus the internal faults of power transformer can be diagnosed accurately as well as its life expectancy updated in time, ensuring that the dynamic assessment values can commendably track and reflect the actual operation state of the power transformers.

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